Coordinated management of multiple interacting resources in chip multiprocessors: A machine learning approach

  • Authors:
  • Ramazan Bitirgen;Engin Ipek;Jose F. Martinez

  • Affiliations:
  • Computer Systems Laboratory, Cornell University, Ithaca, NY 14853 USA;Microsoft Research, Redmond, WA 98052 USA;Computer Systems Laboratory, Cornell University, Ithaca, NY 14853 USA

  • Venue:
  • Proceedings of the 41st annual IEEE/ACM International Symposium on Microarchitecture
  • Year:
  • 2008

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Abstract

Efficient sharing of system resources is critical to obtaining high utilization and enforcing system-level performance objectives on chip multiprocessors (CMPs). Although several proposals that address the management of a single microarchitectural resource have been published in the literature, coordinated management of multiple interacting resources on CMPs remains an open problem.